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ICANN
2009
Springer
14 years 3 months ago
Evolving Memory Cell Structures for Sequence Learning
The best recent supervised sequence learning methods use gradient descent to train networks of miniature nets called memory cells. The most popular cell structure seems somewhat ar...
Justin Bayer, Daan Wierstra, Julian Togelius, J&uu...
CORR
2010
Springer
152views Education» more  CORR 2010»
13 years 9 months ago
Neuroevolutionary optimization
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Eva Volná
BMCBI
2008
174views more  BMCBI 2008»
13 years 9 months ago
Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset
Background: Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interact...
Cédric Auliac, Vincent Frouin, Xavier Gidro...
CEC
2008
IEEE
13 years 11 months ago
Investigation of simply coded evolutionary artificial neural networks on robot control problems
One of the advantages of evolutionary robotics over other approaches in embodied cognitive science would be its parallel population search. Due to the population search, it takes a...
Yoshiaki Katada, Jun Nakazawa
GECCO
2006
Springer
216views Optimization» more  GECCO 2006»
14 years 23 days ago
Comparative analysis of the sailor assignment problem
In this work the performance of several local search and metaheuristic methods is compared to previously reported work using evolutionary algorithms. The results show that while m...
Joseph Vannucci, Deon Garrett, Dipankar Dasgupta